CN108965906A - A kind of video storage method based on cloud storage service device - Google Patents
A kind of video storage method based on cloud storage service device Download PDFInfo
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
- H04N21/23113—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion involving housekeeping operations for stored content, e.g. prioritizing content for deletion because of storage space restrictions
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs
- H04N21/23418—Processing of video elementary streams, e.g. splicing of video streams, manipulating MPEG-4 scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
- H04N21/637—Control signals issued by the client directed to the server or network components
- H04N21/6375—Control signals issued by the client directed to the server or network components for requesting retransmission, e.g. of data packets lost or corrupted during transmission from server
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The present invention discloses a kind of video storage method based on cloud storage service device, includes the following steps: to divide memory space, constitutes set A；The video segment information sent is received, and is divided into several sub-video sections, obtains the time span of the medium and small video-frequency band of sub-video section；The integrity degree for calculating each sub-video section, the sub-video section that will be greater than setting value are stored into set A, and the sub-video section for being less than setting threshold values is returned, video segment information is retransmitted；Compare the storage size of the video segment information of transmission and the storage size of storage set A neutron memory space；The video segment information sent again is extracted, extracts the sub-video segment information for being less than setting threshold values, and detect integrity degree；When receiving next new video segment information, above step is repeated, until storage is completed.The present invention greatly improves the accuracy and integrality of the video of storage, while being convenient for the inquiry of later period video by carrying out integrity degree detection and regular storage to received video segment information.
Description
Technical field
The invention belongs to cloud storage service device technical fields, are related to a kind of video storage based on cloud storage service device
Method.
Background technique
With the development of cloud, every field is also gradually penetrated into cloud storage application, and data explosion increases, magnanimity
The video data that monitoring device generates daily is inestimable, and in public safety field, being investigated into a case by video investigation technology has been
The technology being in daily use.
Along with the landing of Internet of Things application and the rise of average family commercial market, entire security industry market scale
Rapidly grow, driven Video Surveillance Industry technology Continuous Innovation, by initial user to video image data just only see not
Long-time storage till now is deposited or saved on a small quantity, makes video data that the situation of explosive increase be presented, DVR storage originally
Multitude of video data fast storage demand is can not meet with the preservation of server local hard drive, it is urgent to provide a high-performance
Video store product, existing video storage product can not examine received video information during storage
It surveys, causes the integrity degree of received video poor, influence the viewing of later period video, simultaneously because memory space is larger, so that depositing
The process of storage is disorderly and unsystematic, cannot achieve regular storage, is not easy to the inquiry of later period video.
Summary of the invention
The purpose of the present invention is to provide a kind of video storage methods based on cloud storage service device, solve existing cloud
Storage server can not be detected and be detected to the integrity degree for the video that need to be stored, and then cause during video stores
The integrity degree of the video of storage and accuracy are low, are not easy to the observation in later period.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of video storage method based on cloud storage service device, includes the following steps:
S1, the memory space in cloud storage service device is divided, forms several sub- memory spaces, several sub- storages
Space composition storage set A (a1, a2 ..., ai ..., an)；
S2, the video segment information that provisional video memory is sent is received, if T is divided into according to the time period by video segment information
Dry sub-video section B (b1, b2 ..., bj ..., bm), if neglecting frequency range greater than 2S comprising several intervals in the sub-video section,
The time span for neglecting frequency range is counted, t1, t2 ..., ti are obtained, wherein ti is expressed as the time of i-th of small video
Length, and i >=2；
S3, the integrity degree of each sub-video section is calculated, integrity degree is greater than to the sub-video section of setting integrity degree threshold values
It stores into storage set A, the storage order of memory space is the sub- memory space for being followed successively by a1, a2 ..., ai ..., an；
The sub-video section that integrity degree is less than the integrity degree threshold values of setting is successively fed back to according to the received sequence of cloud storage service device and is faced
When video memory, provisional video memory receives the sub-video segment information of feedback, and by the corresponding video-frequency band of sub-video section
Information is re-transmitted to cloud storage service device；
S4, the storage that the storage size for the video segment information that provisional video memory is sent is detected, and will test
Size and the remaining amount of storage of storage set A neutron memory space ai compare, if the residue for storing sub- memory space ai is deposited
Reserves are less than the storage size for the video segment information that provisional video memory is sent, then the integrity degree are greater than integrity degree threshold values
Sub-video segment information store to sub- memory space a (i+1)；
S4, the video segment information sent again is extracted, to extract the integrity degree threshold values that integrity degree is less than setting
Sub-video segment information；
S5, the sub-video segment information in step S4 is subjected to integrity degree detection, obtains integrity degree, the integrity degree that will test
It is compared with the integrity degree threshold values of setting, if integrity degree is greater than the integrity degree threshold values of setting, sub-video segment information storage
To sub- memory space a (i+1)；
If S6, the integrity degree threshold values for being less than setting, repeat to enter step S4 and S5, until the video of the video-frequency band is believed
Breath is sent completely completely；
S7, whenever receiving next new video segment information of provisional video memory transmission, repeat step S2-
S6, until video-frequency band all storage completions that provisional video memory is sent.
Further, the integrity degree calculation formula of the step S3 neutron video-frequency band isWherein, T is son view
The total time length of frequency.
Further, in the step S4 video segment information extraction, comprising the following steps:
(1), judge that integrity degree is less than the front end of the sub-video section of setting integrity degree threshold values and rearmost end whether there is view
Frequency information；
(2) if, front end and rearmost end there is video information, (3) are entered step, if only there is video front end
Information enters step (4), if only rearmost end has video information, enters step (5)；
(3), the video information of front end and rearmost end is intercepted, obtains several picture samples, the video of front end
The corresponding picture sample set C of informationBefore(c1,c2,...,ci,...,cm),DAfterwards(d1, d2 ..., di ..., dn), wherein m
=n, m and n are expressed as the picture sample quantity of the video segment information front end extracted and rearmost end；
(4), the video information of front end is intercepted, obtains several picture samples, the video information of front end is corresponding
Picture sample set CBefore(c1, c2 ..., ci ..., cm), m indicate the picture sample for the video segment information front end extracted
This quantity, and extract the corresponding picture sample set D ' of video segment information away from rearmost end time t 'Afterwards(d1, d2 ...,
Di ..., dn)), n indicates to extract image pattern quantity；
(5), the video information of rearmost end is intercepted, obtains several picture samples, the video information of rearmost end is corresponding
Picture sample set DAfterwards(d1, d2 ..., di ..., dn), and the corresponding picture sample of video segment information for extracting t from the front end "
This set C 'Before(c1, c2 ..., ci ..., cm), m indicate the picture sample quantity extracted；
(6), the image pattern in step S3, S4 or S5 is modeled, iconic model data is converted into, to conversion
Iconic model data carry out the foundation of feature vector, and described eigenvector is that every image pattern is divided into v*v histogram
Picture, and according to sequence from top to bottom and from left to right, be successively set as the 1st feature vector, the 2nd feature vector ..., v*v
Feature vector, several feature vectors constitute set Fi (Fi1, Fi2 ..., Fij ..., Fiv*v), and Fij is expressed as Fi
Corresponding j-th of the feature vector of image pattern, described eigenvector are color, the distributing position etc. of image；
(7), the feature vector after the video segment information conversion for sending the feature vector of foundation and provisional video memory
Registration detection is carried out, the video information that provisional video memory is sent includes several video-frequency bands, constitutes video-frequency band set W
(w1, w2 ..., wh), the image collection in each video-frequency band be C (C1, C2 ..., Ck ..., Cf), f indicates image pattern
Quantity, and each image pattern corresponds to different feature vectors, and the feature vector in each image constitutes collection and is combined into Dk
(Dk1, Dk2 ..., Dkj ..., Dkv*v), Dkj are expressed as corresponding j-th of the feature vector of the Dk image；
(8), corresponding with image in the video segment information that provisional video memory is sent to the feature vector in step (6)
Feature vector compare, constitute be overlapped vector set Bi ' (bi ' 1, bi ' 2 ..., bi ' j ..., bi ' v*v), wherein
Bi ' j indicates the jth in the jth feature vector picture sample corresponding with the video segment information of transmission in the Bi image pattern
The value that feature vector coincides, j-th of feature vector picture sample corresponding with the video segment information of transmission in image pattern
In the value that coincides of j-th of feature vector be 1, be 0 otherwise；
(9), the registration for the video segment information for being less than integrity degree threshold values with integrity degree in the video segment information sent is greater than
The registration threshold values of setting, and the corresponding video-frequency band information extraction of the registration is gone out, and the new video section is carried out to premise
Preceding t " time or backward delay t ' time obtain best video segment information, and the best video segment information obtained enters step
S5。
Further, in the step (8), integrity degree is less than the sub-video segment information and provisional video of integrity degree threshold values
The registration for the corresponding several video segment informations of video segment information that memory is sent calculates,Wherein, G is indicated
Superposition degree modulus,
Beneficial effects of the present invention:
Video storage method provided by the invention based on cloud storage service device, by received video segment information into
The detection of row integrity degree, the video-frequency band that integrity degree is greater than the integrity degree threshold values of setting is stored, to less than integrity degree threshold values
Video-frequency band is received and is detected again, greatly improves the accuracy and integrality of the video of storage, and by believing video-frequency band
Breath carries out regular storage, convenient for the inquiry of later period video.
Specific embodiment
Below in conjunction with the embodiment of the present invention, technical solution in the embodiment of the present invention is clearly and completely retouched
It states, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on the present invention
In embodiment, all other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
The present invention is a kind of video storage method based on cloud storage service device, is included the following steps:
S1, the memory space in cloud storage service device is divided, forms several sub- memory spaces, several sub- storages
Space composition storage set A (a1, a2 ..., ai ..., an)；
S2, receive provisional video memory send video segment information, by video segment information according to the time period T (T > 2s) into
Row divides, and several sub-video section B (b1, b2 ..., bj ..., bm) is divided into, to the complete of the video in several sub-video sections
Degree is detected, if neglecting frequency range greater than 2S comprising several intervals in the sub-video section, to neglect the time span of frequency range into
Row statistics, obtains t1, t2 ..., ti, wherein ti is expressed as the time span of i-th of small video, and i >=2；
S3, the integrity degree of each sub-video section is calculated, integrity degree is greater than to the sub-video section of setting integrity degree threshold values
It stores into storage set A, the storage order of memory space is the sub- memory space for being followed successively by a1, a2 ..., ai ..., an；
The sub-video section that integrity degree is less than the integrity degree threshold values of setting is successively fed back to according to the received sequence of cloud storage service device and is faced
When video memory, provisional video memory receives the sub-video segment information of feedback, and by the corresponding video-frequency band of sub-video section
Information is re-transmitted to cloud storage service device, and wherein the integrity degree calculation formula of sub-video section isWherein, T is
The total time length of sub-video；
S4, the storage that the storage size for the video segment information that provisional video memory is sent is detected, and will test
Size and the remaining amount of storage of storage set A neutron memory space ai compare, if the residue for storing sub- memory space ai is deposited
Reserves are less than the storage size for the video segment information that provisional video memory is sent, then the integrity degree are greater than integrity degree threshold values
Sub-video segment information store to sub- memory space a (i+1)；
S4, the video segment information sent again is extracted, to extract the integrity degree threshold values that integrity degree is less than setting
Sub-video segment information；
S5, the sub-video segment information in step S4 is subjected to integrity degree detection, obtains integrity degree, the integrity degree that will test
It is compared with the integrity degree threshold values of setting, if integrity degree is greater than the integrity degree threshold values of setting, sub-video segment information storage
To sub- memory space a (i+1)；
If S6, the integrity degree threshold values for being less than setting, repeat to enter step S4 and S5；
S7, whenever receiving next new video segment information of provisional video memory transmission, repeat step S2-
S6, until video-frequency band all storage completions that provisional video memory is sent.
Wherein, in step S4 video segment information extraction the following steps are included:
(2), judge that integrity degree is less than the front end of the sub-video section of setting integrity degree threshold values and rearmost end whether there is view
Frequency information；
(2) if, front end and rearmost end there is video information, (3) are entered step, if only there is video front end
Information enters step (4), if only rearmost end has video information, enters step (5)；
(3), the video information of front end and rearmost end is intercepted, obtains several picture samples, the video of front end
The corresponding picture sample set C of informationBefore(c1,c2,...,ci,...,cm),DAfterwards(d1, d2 ..., di ..., dn), wherein m
=n, m and n are expressed as the picture sample quantity of the video segment information front end extracted and rearmost end；
(4), the video information of front end is intercepted, obtains several picture samples, the video information of front end is corresponding
Picture sample set CBefore(c1, c2 ..., ci ..., cm), m indicate the picture sample for the video segment information front end extracted
This quantity, and extract the corresponding picture sample set D ' of video segment information away from rearmost end time t 'Afterwards(d1, d2 ...,
Di ..., dn)), n indicates to extract image pattern quantity；
(5), the video information of rearmost end is intercepted, obtains several picture samples, the video information of rearmost end is corresponding
Picture sample set DAfterwards(d1, d2 ..., di ..., dn), and the corresponding picture sample of video segment information for extracting t from the front end "
This set C 'Before(c1, c2 ..., ci ..., cm), m indicate the picture sample quantity extracted；
(6), the image pattern in step S3, S4 or S5 is modeled, iconic model data is converted into, to conversion
Iconic model data carry out the foundation of feature vector, and described eigenvector is that every image pattern is divided into v*v histogram
Picture, and according to sequence from top to bottom and from left to right, be successively set as the 1st feature vector, the 2nd feature vector ..., v*v
Feature vector, several feature vectors constitute set Fi (Fi1, Fi2 ..., Fij ..., Fiv*v), and Fij is expressed as Fi
Corresponding j-th of the feature vector of image pattern, described eigenvector are color, the distributing position etc. of image；
(7), the feature vector after the video segment information conversion for sending the feature vector of foundation and provisional video memory
Registration detection is carried out, the video information that provisional video memory is sent includes several video-frequency bands, constitutes video-frequency band set W
(w1, w2 ..., wh), the image collection in each video-frequency band be C (C1, C2 ..., Ck ..., Cf), f indicates image pattern
Quantity, and each image pattern corresponds to different feature vectors, and the feature vector in each image constitutes collection and is combined into Dk
(Dk1, Dk2 ..., Dkj ..., Dkv*v), Dkj are expressed as corresponding j-th of the feature vector of the Dk image；
(8), corresponding with image in the video segment information that provisional video memory is sent to the feature vector in step (6)
Feature vector compare, constitute be overlapped vector set Bi ' (bi ' 1, bi ' 2 ..., bi ' j ..., bi ' v*v), wherein
Bi ' j indicates the jth in the jth feature vector picture sample corresponding with the video segment information of transmission in the Bi image pattern
The value that feature vector coincides, j-th of feature vector picture sample corresponding with the video segment information of transmission in image pattern
In the value that coincides of j-th of feature vector be 1, be 0 otherwise；
According to registration calculation formula, sub-video segment information and provisional video that integrity degree is less than integrity degree threshold values are calculated
The registration for the corresponding several video segment informations of video segment information that memory is sent,Wherein, G indicates to be overlapped
Coefficient is spent,
(9), the registration for the video segment information for being less than integrity degree threshold values with integrity degree in the video segment information sent is greater than
The registration threshold values of setting, and the registration is corresponded into video-frequency band information extraction and is gone out, and the new video section is shifted to an earlier date forward
T " time or backward delay t ' time obtain best video segment information, and the best video segment information obtained enters step S5.
The above content is just an example and description of the concept of the present invention, the technology people of affiliated the art
Member makes various modifications or additions to the described embodiments or is substituted in a similar manner, without departing from
The design of invention or beyond the scope defined by this claim, is within the scope of protection of the invention.
Claims (4)
1. a kind of video storage method based on cloud storage service device, which comprises the steps of:
S1, the memory space in cloud storage service device is divided, forms several sub- memory spaces, several sub- memory space structures
At storage set A (a1, a2 ..., ai ..., an)；
S2, the video segment information that provisional video memory is sent is received, T is divided into several sub- views according to the time period by video segment information
Frequency range B (b1, b2 ..., bj ..., bm), if neglecting frequency range greater than 2S comprising several intervals in the sub-video section, to neglecting
The time span of frequency range is counted, and t1, t2 ..., ti are obtained, wherein and ti is expressed as the time span of i-th of small video, and
i≥2；
S3, the integrity degree of each sub-video section is calculated, the sub-video section that integrity degree is greater than setting integrity degree threshold values is stored
Into storage set A, the storage order of memory space is the sub- memory space for being followed successively by a1, a2 ..., ai ..., an；It will be complete
The sub-video section for the integrity degree threshold values that whole degree is less than setting successively feeds back to interim view according to the received sequence of cloud storage service device
Frequency memory, provisional video memory receive the sub-video segment information of feedback, and by the corresponding video segment information of the sub-video section
It is re-transmitted to cloud storage service device；
S4, the storage size that the storage size for the video segment information that provisional video memory is sent is detected, and will test
It is compared with the remaining amount of storage of storage set A neutron memory space ai, if storing the remaining amount of storage of sub- memory space ai
Less than the storage size for the video segment information that provisional video memory is sent, then the son that the integrity degree is greater than integrity degree threshold values is regarded
Band information is stored to sub- memory space a (i+1)；
S4, the video segment information sent again is extracted, to extract the son that integrity degree is less than the integrity degree threshold values of setting
Video segment information；
S5, the sub-video segment information in step S4 is subjected to integrity degree detection, obtains integrity degree, the integrity degree that will test and setting
Integrity degree threshold values compare, if integrity degree be greater than setting integrity degree threshold values, which, which stores to son, deposits
It stores up space a (i+1)；
If S6, the integrity degree threshold values for being less than setting, repeat to enter step S4 and S5, until the video information of the video-frequency band is complete
It is sent completely；
S7, whenever receiving next new video segment information of provisional video memory transmission, repeat step S2-S6, directly
The video-frequency band sent to provisional video memory all complete by storage.
2. a kind of video storage method based on cloud storage service device according to claim 1, it is characterised in that: the step
Suddenly the integrity degree calculation formula of S3 neutron video-frequency band isWherein, T is the total time length of sub-video.
3. a kind of video storage method based on cloud storage service device according to claim 1, it is characterised in that: the step
The extraction of video segment information in rapid S4, comprising the following steps:
(1), judge that integrity degree is less than the front end of the sub-video section of setting integrity degree threshold values and rearmost end is believed with the presence or absence of video
Breath；
(2) if, front end and rearmost end there is video information, enter step (3), if only there is video information front end,
(4) are entered step, if only rearmost end has video information, enter step (5)；
(3), the video information of front end and rearmost end is intercepted, obtains several picture samples, the video information of front end
Corresponding picture sample set CBefore(c1,c2,...,ci,...,cm),DAfterwards(d1, d2 ..., di ..., dn), wherein m=n, m
The picture sample quantity of the video segment information front end extracted and rearmost end is expressed as with n；
(4), the video information of front end is intercepted, obtains several picture samples, the corresponding figure of the video information of front end
Piece sample set CBefore(c1, c2 ..., ci ..., cm), m indicate the picture sample number for the video segment information front end extracted
Amount, and extract the corresponding picture sample set D ' of video segment information away from rearmost end time t 'Afterwards(d1, d2 ..., di ...,
Dn)), n indicates to extract image pattern quantity；
(5), the video information of rearmost end is intercepted, obtains several picture samples, the corresponding figure of the video information of rearmost end
Piece sample set DAfterwards(d1, d2 ..., di ..., dn), and the corresponding picture sample collection of video segment information for extracting t from the front end "
Close C 'Before(c1, c2 ..., ci ..., cm), m indicate the picture sample quantity extracted；
(6), the image pattern in step S3, S4 or S5 is modeled, is converted into iconic model data, to the image mould of conversion
Type data carry out the foundation of feature vector, and described eigenvector is every image pattern to be divided into v*v rectangular image, and press
According to sequence from top to bottom and from left to right, be successively set as the 1st feature vector, the 2nd feature vector ..., v*v feature vector,
Several feature vectors constitute set Fi (Fi1, Fi2 ..., Fij ..., Fiv*v), and it is corresponding that Fij is expressed as the Fi image pattern
J-th of feature vector, described eigenvector be image color, distributing position etc.；
(7), the feature vector progress after the video segment information conversion for sending the feature vector of foundation and provisional video memory
Registration detection, the video information that provisional video memory is sent includes several video-frequency bands, composition video-frequency band set W (w1,
W2 ..., wh), the image collection in each video-frequency band be C (C1, C2 ..., Ck ..., Cf), f indicates the number of image pattern
Amount, and each image pattern correspond to different feature vectors, the feature vector in each image constitute collect be combined into Dk (Dk1,
Dk2 ..., Dkj ..., Dkv*v), Dkj is expressed as corresponding j-th of the feature vector of the Dk image；
(8), to the feature vector feature corresponding with image in the video segment information that provisional video memory is sent in step (6)
Vector compares, and constitutes and is overlapped vector set Bi ' (bi ' 1, bi ' 2 ..., bi ' j ..., bi ' v*v), wherein bi ' j is indicated
The jth feature vector in jth feature vector picture sample corresponding with the video segment information of transmission in the Bi image pattern
The value to coincide, j-th in j-th of feature vector picture sample corresponding with the video segment information of transmission in image pattern
The value that feature vector coincides is 1, is 0 otherwise；
(9), the registration for being less than the video segment information of integrity degree threshold values in the video segment information sent with integrity degree is greater than setting
Registration threshold values, and the corresponding video-frequency band information extraction of the registration is gone out, and the new video section is carried out to shift to an earlier date t " forward
Time or backward delay t ' time obtain best video segment information, and the best video segment information obtained enters step S5.
4. a kind of video storage method based on cloud storage service device according to claim 3, it is characterised in that: the step
Suddenly in (8), integrity degree is less than the sub-video segment information of integrity degree threshold values and the video segment information pair of provisional video memory transmission
The registration for several video segment informations answered calculates,Wherein, G indicates Superposition degree modulus,
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810524259.4A CN108965906B (en) | 2018-05-28 | 2018-05-28 | Video storage method based on cloud storage server |
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